diff --git a/main_multi.py b/main_multi.py
index 41b9efd..b7b2208 100644
--- a/main_multi.py
+++ b/main_multi.py
@@ -81,6 +81,21 @@ def main():
     for idx in selected_indices:
         group = groups[idx]
         logger.info(f"  • {group['name']} (串口:{group['serial_port']}, 采集卡:{group['camera_index']})")
+
+    # 串口冲突预检：同一串口被多个组占用通常会导致仅一路成功
+    port_to_groups = {}
+    for idx in selected_indices:
+        g = groups[idx]
+        port_to_groups.setdefault(g['serial_port'], []).append(g['name'])
+    conflicts = {p: names for p, names in port_to_groups.items() if p and len(names) > 1}
+    if conflicts:
+        logger.warning("⚠️ 检测到串口冲突（同一COM被多个组使用）：")
+        for p, names in conflicts.items():
+            logger.warning(f"  {p}: {', '.join(names)}")
+        go_on = input("上述冲突很可能导致仅一组成功，其它失败。仍要继续? (y/n): ").strip().lower()
+        if go_on != 'y':
+            logger.info("已取消启动以避免串口冲突")
+            return
     
     confirm = input("\n确认启动? (y/n): ").strip().lower()
     if confirm != 'y':
diff --git a/test_capture_card.py b/test_capture_card.py
new file mode 100644
index 0000000..9510d07
--- /dev/null
+++ b/test_capture_card.py
@@ -0,0 +1,796 @@
+"""
+采集卡截图测试类
+用于测试采集卡的分辨率和色差
+保持与实际代码相同的实现逻辑
+"""
+import time
+import threading
+import warnings
+import os
+import sys
+import io
+import cv2
+import numpy as np
+from PIL import Image
+from utils.logger import logger, throttle
+import logging
+
+# 抑制OpenCV的警告信息（兼容不同版本）
+os.environ['OPENCV_LOG_LEVEL'] = 'SILENT'
+os.environ['OPENCV_IO_ENABLE_OPENEXR'] = '0'
+
+try:
+    if hasattr(cv2, 'setLogLevel'):
+        if hasattr(cv2, 'LOG_LEVEL_SILENT'):
+            cv2.setLogLevel(cv2.LOG_LEVEL_SILENT)
+        elif hasattr(cv2, 'LOG_LEVEL_ERROR'):
+            cv2.setLogLevel(cv2.LOG_LEVEL_ERROR)
+        elif hasattr(cv2, 'utils'):
+            cv2.utils.setLogLevel(0)
+except Exception:
+    pass
+
+
+class CaptureCardTester:
+    """
+    采集卡测试类
+    使用与实际代码相同的实现逻辑
+    """
+    
+    def __init__(self, cam_index=0, width=1920, height=1080):
+        """
+        初始化采集卡测试器
+        :param cam_index: 采集卡索引
+        :param width: 期望宽度
+        :param height: 期望高度
+        """
+        logger.info(f"🔧 正在初始化采集卡测试器 {cam_index}...")
+        self.cap = None
+        self.frame = None
+        self.running = True
+        self.cam_index = cam_index
+        self.expected_width = width
+        self.expected_height = height
+        self.actual_width = None
+        self.actual_height = None
+        
+        # 尝试多种方式打开采集卡（与实际代码相同）
+        backends_to_try = [
+            (cam_index, cv2.CAP_DSHOW),
+            (cam_index, cv2.CAP_ANY),
+            (cam_index, None),  # 默认后端
+        ]
+        
+        # 重定向stderr来抑制OpenCV的错误输出
+        old_stderr = sys.stderr
+        suppressed_output = io.StringIO()
+        
+        try:
+            sys.stderr = suppressed_output
+            
+            for idx, backend in backends_to_try:
+                try:
+                    with warnings.catch_warnings():
+                        warnings.filterwarnings('ignore', category=UserWarning)
+                        if backend is not None:
+                            self.cap = cv2.VideoCapture(idx, backend)
+                        else:
+                            self.cap = cv2.VideoCapture(idx)
+                    
+                    if self.cap.isOpened():
+                        # 测试读取一帧
+                        ret, test_frame = self.cap.read()
+                        if ret and test_frame is not None:
+                            logger.info(f"✅ 采集卡 {cam_index} 打开成功")
+                            break
+                        else:
+                            self.cap.release()
+                            self.cap = None
+                except Exception as e:
+                    if self.cap:
+                        try:
+                            self.cap.release()
+                        except:
+                            pass
+                        self.cap = None
+                    continue
+        finally:
+            # 恢复stderr
+            sys.stderr = old_stderr
+        
+        if self.cap is None or not self.cap.isOpened():
+            logger.error(f"❌ 无法打开采集卡 {cam_index}")
+            logger.error("请检查：\n  1. 采集卡是否正确连接\n  2. 采集卡索引是否正确（尝试扫描采集卡）\n  3. 采集卡驱动是否安装\n  4. 采集卡是否被其他程序占用")
+            self.cap = None
+            return
+        
+        # 设置分辨率（与实际代码相同）
+        try:
+            self.cap.set(cv2.CAP_PROP_FRAME_WIDTH, width)
+            self.cap.set(cv2.CAP_PROP_FRAME_HEIGHT, height)
+            # 实际获取设置后的分辨率
+            self.actual_width = int(self.cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+            self.actual_height = int(self.cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+            logger.info(f"   分辨率设置: {width}x{height} -> 实际: {self.actual_width}x{self.actual_height}")
+        except Exception as e:
+            logger.warning(f"⚠️ 设置分辨率失败: {e}")
+        
+        # 启动更新线程（与实际代码相同）
+        threading.Thread(target=self.update, daemon=True).start()
+        
+        # 等待几帧确保采集卡正常工作
+        time.sleep(1.0)
+        logger.info(f"✅ 采集卡 {cam_index} 初始化完成")
+    
+    def update(self):
+        """持续更新帧（与实际代码相同）"""
+        while self.running and self.cap is not None:
+            try:
+                ret, frame = self.cap.read()
+                if ret and frame is not None:
+                    self.frame = frame
+                    # 限制读取频率，避免占满CPU
+                    time.sleep(0.008)
+                else:
+                    # 读取失败时不打印，避免刷屏
+                    time.sleep(0.02)
+            except Exception as e:
+                # 只在异常时打印错误
+                throttle(f"cap_read_err_{self.cam_index}", 2.0, logging.WARNING, f"⚠️ 采集卡 {self.cam_index} 读取异常: {e}")
+                time.sleep(0.1)  # 出错时短暂延迟
+    
+    def get_frame(self):
+        """
+        获取处理后的帧（与实际代码相同）
+        返回: [im_opencv, im_PIL] 或 None
+        """
+        if self.cap is None or self.frame is None:
+            return None
+        try:
+            im_opencv = cv2.cvtColor(self.frame, cv2.COLOR_BGR2RGB)
+            im_opencv = im_opencv[30:30+720, 0:1280]  # 裁剪尺寸（与实际代码相同）
+            im_PIL = Image.fromarray(im_opencv)
+            return [im_opencv, im_PIL]
+        except Exception as e:
+            throttle(f"img_proc_err_{self.cam_index}", 2.0, logging.WARNING, f"⚠️ 图像处理错误: {e}")
+            return None
+    
+    def get_raw_frame(self):
+        """
+        获取原始帧（未裁剪）
+        返回: numpy array 或 None
+        """
+        if self.cap is None or self.frame is None:
+            return None
+        return self.frame.copy()
+    
+    def test_resolution(self):
+        """
+        测试分辨率
+        返回分辨率信息字典
+        """
+        if self.cap is None:
+            logger.error("采集卡未初始化")
+            return None
+        
+        result = {
+            'expected': (self.expected_width, self.expected_height),
+            'actual_cap': (self.actual_width, self.actual_height),
+            'actual_frame': None,
+            'cropped_frame': None,
+            'match': False
+        }
+        
+        # 获取原始帧尺寸
+        raw_frame = self.get_raw_frame()
+        if raw_frame is not None:
+            h, w = raw_frame.shape[:2]
+            result['actual_frame'] = (w, h)
+        
+        # 获取裁剪后帧尺寸
+        processed = self.get_frame()
+        if processed is not None:
+            im_opencv = processed[0]
+            h, w = im_opencv.shape[:2]
+            result['cropped_frame'] = (w, h)
+        
+        # 检查分辨率是否匹配
+        if result['actual_cap'] is not None:
+            result['match'] = (result['actual_cap'][0] == self.expected_width and 
+                             result['actual_cap'][1] == self.expected_height)
+        
+        return result
+    
+    def test_color_difference(self, frame1=None, frame2=None):
+        """
+        测试色差
+        :param frame1: 第一帧（可选，不提供则使用当前帧）
+        :param frame2: 第二帧（可选，不提供则等待一帧后获取）
+        :return: 色差信息字典
+        """
+        if frame1 is None:
+            frame1 = self.get_frame()
+            if frame1 is None:
+                logger.error("无法获取第一帧")
+                return None
+            frame1 = frame1[0]  # 使用opencv格式
+        
+        if frame2 is None:
+            # 等待一小段时间获取新帧
+            time.sleep(0.1)
+            frame2 = self.get_frame()
+            if frame2 is None:
+                logger.error("无法获取第二帧")
+                return None
+            frame2 = frame2[0]  # 使用opencv格式
+        
+        # 确保两帧尺寸相同
+        if frame1.shape != frame2.shape:
+            logger.warning(f"两帧尺寸不同: {frame1.shape} vs {frame2.shape}")
+            # 调整尺寸
+            h, w = min(frame1.shape[0], frame2.shape[0]), min(frame1.shape[1], frame2.shape[1])
+            frame1 = frame1[:h, :w]
+            frame2 = frame2[:h, :w]
+        
+        # 计算色差
+        diff = cv2.absdiff(frame1, frame2)
+        diff_gray = cv2.cvtColor(diff, cv2.COLOR_RGB2GRAY)
+        
+        # 计算统计信息
+        mean_diff = np.mean(diff)
+        std_diff = np.std(diff)
+        max_diff = np.max(diff)
+        mean_diff_gray = np.mean(diff_gray)
+        
+        # 计算RGB各通道的平均色差
+        mean_diff_r = np.mean(diff[:, :, 0])
+        mean_diff_g = np.mean(diff[:, :, 1])
+        mean_diff_b = np.mean(diff[:, :, 2])
+        
+        # 计算PSNR（峰值信噪比）
+        mse = np.mean((frame1.astype(float) - frame2.astype(float)) ** 2)
+        if mse == 0:
+            psnr = float('inf')
+        else:
+            psnr = 20 * np.log10(255.0 / np.sqrt(mse))
+        
+        result = {
+            'mean_diff': float(mean_diff),
+            'std_diff': float(std_diff),
+            'max_diff': int(max_diff),
+            'mean_diff_gray': float(mean_diff_gray),
+            'mean_diff_r': float(mean_diff_r),
+            'mean_diff_g': float(mean_diff_g),
+            'mean_diff_b': float(mean_diff_b),
+            'psnr': float(psnr),
+            'mse': float(mse),
+            'diff_image': diff,
+            'diff_gray': diff_gray
+        }
+        
+        return result
+    
+    def test_color_stability(self, num_frames=10, interval=0.1):
+        """
+        测试颜色稳定性（连续多帧的色差）
+        :param num_frames: 测试帧数
+        :param interval: 帧间隔（秒）
+        :return: 稳定性统计信息
+        """
+        frames = []
+        logger.info(f"开始采集 {num_frames} 帧用于稳定性测试...")
+        
+        for i in range(num_frames):
+            frame = self.get_frame()
+            if frame is None:
+                logger.warning(f"无法获取第 {i+1} 帧")
+                continue
+            frames.append(frame[0])  # 使用opencv格式
+            if i < num_frames - 1:
+                time.sleep(interval)
+        
+        if len(frames) < 2:
+            logger.error("采集的帧数不足")
+            return None
+        
+        # 计算所有帧之间的平均色差
+        all_diffs = []
+        for i in range(len(frames) - 1):
+            diff_result = self.test_color_difference(frames[i], frames[i+1])
+            if diff_result:
+                all_diffs.append(diff_result['mean_diff'])
+        
+        if not all_diffs:
+            return None
+        
+        result = {
+            'num_frames': len(frames),
+            'avg_mean_diff': float(np.mean(all_diffs)),
+            'std_mean_diff': float(np.std(all_diffs)),
+            'min_mean_diff': float(np.min(all_diffs)),
+            'max_mean_diff': float(np.max(all_diffs)),
+            'all_diffs': [float(d) for d in all_diffs]
+        }
+        
+        return result
+    
+    def print_resolution_test(self):
+        """打印分辨率测试结果"""
+        print("\n" + "="*60)
+        print("分辨率测试结果")
+        print("="*60)
+        result = self.test_resolution()
+        if result is None:
+            print("❌ 测试失败：采集卡未初始化")
+            return
+        
+        print(f"期望分辨率: {result['expected'][0]} x {result['expected'][1]}")
+        if result['actual_cap']:
+            print(f"实际分辨率(采集卡): {result['actual_cap'][0]} x {result['actual_cap'][1]}")
+            match_str = "✅ 匹配" if result['match'] else "❌ 不匹配"
+            print(f"分辨率匹配: {match_str}")
+        
+        if result['actual_frame']:
+            print(f"实际分辨率(原始帧): {result['actual_frame'][0]} x {result['actual_frame'][1]}")
+        
+        if result['cropped_frame']:
+            print(f"裁剪后分辨率: {result['cropped_frame'][0]} x {result['cropped_frame'][1]}")
+        print("="*60 + "\n")
+    
+    def print_color_test(self):
+        """打印色差测试结果"""
+        print("\n" + "="*60)
+        print("色差测试结果（两帧对比）")
+        print("="*60)
+        result = self.test_color_difference()
+        if result is None:
+            print("❌ 测试失败：无法获取帧")
+            return
+        
+        print(f"平均色差: {result['mean_diff']:.2f}")
+        print(f"色差标准差: {result['std_diff']:.2f}")
+        print(f"最大色差: {result['max_diff']}")
+        print(f"灰度平均色差: {result['mean_diff_gray']:.2f}")
+        print(f"\nRGB通道平均色差:")
+        print(f"  R通道: {result['mean_diff_r']:.2f}")
+        print(f"  G通道: {result['mean_diff_g']:.2f}")
+        print(f"  B通道: {result['mean_diff_b']:.2f}")
+        print(f"\nPSNR (峰值信噪比): {result['psnr']:.2f} dB")
+        print(f"MSE (均方误差): {result['mse']:.2f}")
+        print("="*60 + "\n")
+    
+    def print_stability_test(self, num_frames=10):
+        """打印稳定性测试结果"""
+        print("\n" + "="*60)
+        print(f"颜色稳定性测试结果（{num_frames}帧）")
+        print("="*60)
+        result = self.test_color_stability(num_frames)
+        if result is None:
+            print("❌ 测试失败：无法获取足够的帧")
+            return
+        
+        print(f"测试帧数: {result['num_frames']}")
+        print(f"平均色差均值: {result['avg_mean_diff']:.2f}")
+        print(f"色差标准差: {result['std_mean_diff']:.2f}")
+        print(f"最小色差: {result['min_mean_diff']:.2f}")
+        print(f"最大色差: {result['max_mean_diff']:.2f}")
+        print(f"\n各帧间色差: {[f'{d:.2f}' for d in result['all_diffs']]}")
+        print("="*60 + "\n")
+    
+    def save_test_images(self, save_dir="test_output"):
+        """保存测试图像"""
+        os.makedirs(save_dir, exist_ok=True)
+        
+        # 保存原始帧
+        raw_frame = self.get_raw_frame()
+        if raw_frame is not None:
+            cv2.imwrite(os.path.join(save_dir, "raw_frame.jpg"), raw_frame)
+            logger.info(f"已保存原始帧: {save_dir}/raw_frame.jpg")
+        
+        # 保存处理后的帧
+        processed = self.get_frame()
+        if processed is not None:
+            cv2.imwrite(os.path.join(save_dir, "processed_frame.jpg"), cv2.cvtColor(processed[0], cv2.COLOR_RGB2BGR))
+            logger.info(f"已保存处理后帧: {save_dir}/processed_frame.jpg")
+        
+        # 保存色差图
+        color_diff = self.test_color_difference()
+        if color_diff is not None:
+            cv2.imwrite(os.path.join(save_dir, "color_diff.jpg"), cv2.cvtColor(color_diff['diff_image'], cv2.COLOR_RGB2BGR))
+            cv2.imwrite(os.path.join(save_dir, "color_diff_gray.jpg"), color_diff['diff_gray'])
+            logger.info(f"已保存色差图: {save_dir}/color_diff.jpg")
+            logger.info(f"已保存灰度色差图: {save_dir}/color_diff_gray.jpg")
+    
+    def release(self):
+        """释放资源（与实际代码相同）"""
+        self.running = False
+        time.sleep(0.2)
+        if self.cap is not None:
+            self.cap.release()
+        cv2.destroyAllWindows()
+        logger.info("🔚 采集卡已释放")
+    
+    def __del__(self):
+        """析构函数（与实际代码相同）"""
+        if hasattr(self, "cap") and self.cap is not None:
+            try:
+                self.release()
+            except:
+                pass
+
+
+class MultiCaptureCardTester:
+    """
+    多采集卡测试管理器
+    支持同时测试多张采集卡
+    """
+    
+    def __init__(self):
+        """初始化多采集卡测试管理器"""
+        self.testers = {}  # {cam_index: CaptureCardTester}
+        self.config = None
+    
+    def load_from_config(self):
+        """从配置文件加载采集卡"""
+        try:
+            from config import config_manager
+            config_manager.load_config()
+            self.config = config_manager.config
+            
+            groups = self.config.get('groups', [])
+            if not groups:
+                logger.warning("配置文件中没有找到配置组")
+                return []
+            
+            # 获取所有配置组中的采集卡
+            camera_configs = []
+            for group in groups:
+                cam_idx = group.get('camera_index')
+                cam_width = group.get('camera_width', 1920)
+                cam_height = group.get('camera_height', 1080)
+                name = group.get('name', f"配置组{groups.index(group)}")
+                
+                # 检查是否已存在相同索引的采集卡
+                if cam_idx not in [c['index'] for c in camera_configs]:
+                    camera_configs.append({
+                        'index': cam_idx,
+                        'width': cam_width,
+                        'height': cam_height,
+                        'name': name,
+                        'group': group
+                    })
+            
+            return camera_configs
+        except Exception as e:
+            logger.error(f"从配置加载失败: {e}")
+            return []
+    
+    def add_camera(self, cam_index, width=1920, height=1080, name=None):
+        """
+        添加一张采集卡到测试列表
+        :param cam_index: 采集卡索引
+        :param width: 宽度
+        :param height: 高度
+        :param name: 采集卡名称（可选）
+        """
+        if name is None:
+            name = f"采集卡{cam_index}"
+        
+        if cam_index in self.testers:
+            logger.warning(f"采集卡 {cam_index} 已存在，将重新初始化")
+            self.testers[cam_index].release()
+        
+        tester = CaptureCardTester(cam_index=cam_index, width=width, height=height)
+        if tester.cap is not None:
+            tester.name = name
+            self.testers[cam_index] = tester
+            return True
+        else:
+            logger.error(f"无法初始化采集卡 {cam_index}")
+            return False
+    
+    def initialize_from_config(self, use_all_groups=True):
+        """
+        从配置初始化所有采集卡
+        :param use_all_groups: 是否使用所有配置组，False则只使用活动配置组
+        """
+        camera_configs = self.load_from_config()
+        
+        if not camera_configs:
+            logger.warning("没有找到可用的采集卡配置")
+            return False
+        
+        # 筛选配置组
+        if not use_all_groups:
+            camera_configs = [c for c in camera_configs if c.get('group', {}).get('active', False)]
+            if not camera_configs:
+                logger.warning("没有活动的配置组")
+                return False
+        
+        logger.info(f"📷 找到 {len(camera_configs)} 张采集卡配置")
+        
+        success_count = 0
+        for config in camera_configs:
+            if self.add_camera(
+                cam_index=config['index'],
+                width=config['width'],
+                height=config['height'],
+                name=config['name']
+            ):
+                success_count += 1
+        
+        logger.info(f"✅ 成功初始化 {success_count}/{len(camera_configs)} 张采集卡")
+        return success_count > 0
+    
+    def test_all_resolution(self):
+        """测试所有采集卡的分辨率"""
+        print("\n" + "="*60)
+        print("所有采集卡分辨率测试")
+        print("="*60)
+        
+        results = {}
+        for cam_index, tester in self.testers.items():
+            name = getattr(tester, 'name', f"采集卡{cam_index}")
+            print(f"\n【{name} (索引: {cam_index})】")
+            result = tester.test_resolution()
+            results[cam_index] = result
+        
+        # 汇总结果
+        print("\n" + "-"*60)
+        print("分辨率测试汇总")
+        print("-"*60)
+        for cam_index, result in results.items():
+            if result is None:
+                continue
+            name = getattr(self.testers[cam_index], 'name', f"采集卡{cam_index}")
+            match_str = "✅" if result.get('match', False) else "❌"
+            print(f"{match_str} {name}: 期望{result['expected']} -> 实际{result.get('actual_cap', 'N/A')}")
+        
+        return results
+    
+    def test_all_color(self):
+        """测试所有采集卡的色差"""
+        print("\n" + "="*60)
+        print("所有采集卡色差测试")
+        print("="*60)
+        
+        results = {}
+        for cam_index, tester in self.testers.items():
+            name = getattr(tester, 'name', f"采集卡{cam_index}")
+            print(f"\n【{name} (索引: {cam_index})】")
+            result = tester.test_color_difference()
+            results[cam_index] = result
+        
+        # 汇总结果
+        print("\n" + "-"*60)
+        print("色差测试汇总")
+        print("-"*60)
+        for cam_index, result in results.items():
+            if result is None:
+                continue
+            name = getattr(self.testers[cam_index], 'name', f"采集卡{cam_index}")
+            print(f"{name}: 平均色差={result['mean_diff']:.2f}, PSNR={result['psnr']:.2f}dB")
+        
+        return results
+    
+    def test_all_stability(self, num_frames=10):
+        """测试所有采集卡的稳定性"""
+        print("\n" + "="*60)
+        print("所有采集卡稳定性测试")
+        print("="*60)
+        
+        results = {}
+        for cam_index, tester in self.testers.items():
+            name = getattr(tester, 'name', f"采集卡{cam_index}")
+            print(f"\n【{name} (索引: {cam_index})】")
+            result = tester.test_color_stability(num_frames=num_frames)
+            results[cam_index] = result
+        
+        # 汇总结果
+        print("\n" + "-"*60)
+        print("稳定性测试汇总")
+        print("-"*60)
+        for cam_index, result in results.items():
+            if result is None:
+                continue
+            name = getattr(self.testers[cam_index], 'name', f"采集卡{cam_index}")
+            print(f"{name}: 平均色差={result['avg_mean_diff']:.2f}±{result['std_mean_diff']:.2f}")
+        
+        return results
+    
+    def save_all_test_images(self, base_dir="test_output"):
+        """保存所有采集卡的测试图像"""
+        for cam_index, tester in self.testers.items():
+            name = getattr(tester, 'name', f"采集卡{cam_index}")
+            # 清理名称中的特殊字符，用于目录名
+            safe_name = "".join(c for c in name if c.isalnum() or c in (' ', '-', '_')).rstrip()
+            save_dir = os.path.join(base_dir, safe_name)
+            tester.save_test_images(save_dir=save_dir)
+    
+    def release_all(self):
+        """释放所有采集卡"""
+        for tester in self.testers.values():
+            try:
+                tester.release()
+            except:
+                pass
+        self.testers.clear()
+    
+    def __del__(self):
+        """析构函数"""
+        self.release_all()
+
+
+def scan_cameras(max_index=10):
+    """
+    扫描可用的采集卡
+    :param max_index: 最大扫描索引
+    :return: 可用采集卡索引列表
+    """
+    print("🔍 正在扫描采集卡...")
+    available = []
+    
+    old_stderr = sys.stderr
+    suppressed_output = io.StringIO()
+    
+    try:
+        sys.stderr = suppressed_output
+        
+        for i in range(max_index):
+            cap = None
+            try:
+                with warnings.catch_warnings():
+                    warnings.filterwarnings('ignore')
+                    cap = cv2.VideoCapture(i, cv2.CAP_DSHOW)
+                    if cap.isOpened():
+                        ret, frame = cap.read()
+                        if ret and frame is not None:
+                            available.append(i)
+                            print(f"  ✅ 找到采集卡: 索引 {i}")
+                if cap:
+                    cap.release()
+            except:
+                if cap:
+                    try:
+                        cap.release()
+                    except:
+                        pass
+    finally:
+        sys.stderr = old_stderr
+    
+    if not available:
+        print("  ❌ 未找到可用的采集卡")
+    else:
+        print(f"✅ 共找到 {len(available)} 张采集卡")
+    
+    return available
+
+
+def main():
+    """主测试函数"""
+    print("="*60)
+    print("采集卡截图测试工具（支持多采集卡）")
+    print("="*60)
+    
+    multi_tester = MultiCaptureCardTester()
+    
+    # 选择测试模式
+    print("\n选择测试模式:")
+    print("  1. 从配置文件加载（所有配置组）")
+    print("  2. 从配置文件加载（仅活动配置组）")
+    print("  3. 手动指定采集卡索引")
+    print("  4. 扫描采集卡")
+    print("  0. 退出")
+    
+    choice = input("\n请选择 (0-4): ").strip()
+    
+    if choice == "0":
+        print("👋 退出")
+        return
+    elif choice == "1":
+        # 从配置加载所有配置组
+        if not multi_tester.initialize_from_config(use_all_groups=True):
+            print("❌ 无法从配置初始化采集卡")
+            return
+    elif choice == "2":
+        # 从配置加载活动配置组
+        if not multi_tester.initialize_from_config(use_all_groups=False):
+            print("❌ 无法从配置初始化采集卡")
+            return
+    elif choice == "3":
+        # 手动指定
+        indices_input = input("请输入采集卡索引(用逗号分隔,如: 0,1,2): ").strip()
+        try:
+            indices = [int(x.strip()) for x in indices_input.split(',')]
+            width_input = input("请输入宽度 (默认1920): ").strip()
+            height_input = input("请输入高度 (默认1080): ").strip()
+            width = int(width_input) if width_input else 1920
+            height = int(height_input) if height_input else 1080
+            
+            success_count = 0
+            for idx in indices:
+                if multi_tester.add_camera(idx, width=width, height=height):
+                    success_count += 1
+            
+            if success_count == 0:
+                print("❌ 无法初始化任何采集卡")
+                return
+        except ValueError:
+            print("❌ 输入格式错误")
+            return
+    elif choice == "4":
+        # 扫描采集卡
+        available = scan_cameras()
+        if not available:
+            return
+        
+        indices_input = input(f"请输入要测试的采集卡索引(用逗号分隔,可用: {available}): ").strip()
+        try:
+            indices = [int(x.strip()) for x in indices_input.split(',')]
+            # 验证索引有效性
+            indices = [i for i in indices if i in available]
+            if not indices:
+                print("❌ 没有有效的采集卡索引")
+                return
+            
+            width_input = input("请输入宽度 (默认1920): ").strip()
+            height_input = input("请输入高度 (默认1080): ").strip()
+            width = int(width_input) if width_input else 1920
+            height = int(height_input) if height_input else 1080
+            
+            success_count = 0
+            for idx in indices:
+                if multi_tester.add_camera(idx, width=width, height=height):
+                    success_count += 1
+            
+            if success_count == 0:
+                print("❌ 无法初始化任何采集卡")
+                return
+        except ValueError:
+            print("❌ 输入格式错误")
+            return
+    else:
+        print("❌ 无效选择")
+        return
+    
+    if not multi_tester.testers:
+        print("❌ 没有可用的采集卡")
+        return
+    
+    try:
+        # 等待采集卡稳定
+        print("\n等待采集卡稳定...")
+        time.sleep(1.0)
+        
+        # 测试分辨率
+        multi_tester.test_all_resolution()
+        
+        # 等待一下确保采集卡稳定
+        time.sleep(0.5)
+        
+        # 测试色差
+        multi_tester.test_all_color()
+        
+        # 测试稳定性
+        multi_tester.test_all_stability(num_frames=10)
+        
+        # 保存测试图像
+        multi_tester.save_all_test_images()
+        
+        print("\n✅ 所有测试完成！")
+        print("按 Enter 键退出...")
+        input()
+        
+    except KeyboardInterrupt:
+        print("\n\n用户中断测试")
+    except Exception as e:
+        logger.error(f"测试过程中发生错误: {e}")
+        import traceback
+        traceback.print_exc()
+    finally:
+        multi_tester.release_all()
+
+
+if __name__ == "__main__":
+    main()
+
diff --git a/yolo_test.py b/yolo_test.py
index 58c4435..b58c497 100644
--- a/yolo_test.py
+++ b/yolo_test.py
@@ -1,55 +1,377 @@
 import cv2
-from utils.get_image import get_image
+from utils.get_image import GetImage
 from ultralytics import YOLO
+from config import config_manager
+from utils.logger import logger
+import os
+import numpy as np
 
-model = YOLO(r"best0.pt").to('cuda')
+# 检查模型文件是否存在
+model_path = r"best0.pt"
+if not os.path.exists(model_path):
+    print(f"❌ 模型文件不存在: {model_path}")
+    exit(1)
 
-def yolo_shibie(im_PIL, detections):
-    results = model(im_PIL)
-    result = results[0]
+# 加载YOLO模型
+try:
+    model = YOLO(model_path).to('cuda')
+    print(f"✅ 模型加载成功: {model_path}")
+except Exception as e:
+    print(f"❌ 模型加载失败: {e}")
+    exit(1)
 
-    # ✅ 获取绘制好框的图像
-    frame_with_boxes = result.plot()
+def enhance_sharpness(image, strength=1.5):
+    """
+    增强图像锐度
+    :param image: 输入图像（BGR格式）
+    :param strength: 锐化强度（1.0-3.0，默认1.5）
+    :return: 锐化后的图像
+    """
+    # 创建锐化核
+    kernel = np.array([[-1, -1, -1],
+                       [-1,  9*strength, -1],
+                       [-1, -1, -1]]) / (9*strength - 8)
+    sharpened = cv2.filter2D(image, -1, kernel)
+    return sharpened
 
-    # ✅ 用 OpenCV 动态显示
-    cv2.imshow("YOLO实时检测", frame_with_boxes)
 
-    # ESC 或 Q 键退出
-    if cv2.waitKey(1) & 0xFF in [27, ord('q')]:
-        return None
+def enhance_contrast(image, alpha=1.2, beta=10):
+    """
+    增强对比度和亮度
+    :param image: 输入图像
+    :param alpha: 对比度控制（1.0-3.0，默认1.2）
+    :param beta: 亮度控制（-100到100，默认10）
+    :return: 增强后的图像
+    """
+    return cv2.convertScaleAbs(image, alpha=alpha, beta=beta)
 
-    # ✅ 提取检测信息
-    for i in range(len(result.boxes.xyxy)):
-        left, top, right, bottom = result.boxes.xyxy[i]
-        cls_id = int(result.boxes.cls[i])
-        label = result.names[cls_id]
 
-        if label in ['center', 'next', 'npc1', 'npc2', 'npc3', 'npc4', 'boss', 'zhaozi']:
-            player_x = int(left + (right - left) / 2) + 3
-            player_y = int(top + (bottom - top) / 2) + 40
-            detections[label] = [player_x, player_y]
-        elif label in ['daojv', 'gw']:
-            player_x = int(left + (right - left) / 2) + 3
-            player_y = int(top + (bottom - top) / 2) + 40
-            detections[label].append([player_x, player_y])
+def denoise_image(image, method='bilateral'):
+    """
+    去噪处理
+    :param image: 输入图像
+    :param method: 去噪方法 ('bilateral', 'gaussian', 'fastNlMeans')
+    :return: 去噪后的图像
+    """
+    if method == 'bilateral':
+        # 双边滤波，保留边缘的同时去噪
+        return cv2.bilateralFilter(image, 9, 75, 75)
+    elif method == 'gaussian':
+        # 高斯模糊去噪
+        return cv2.GaussianBlur(image, (5, 5), 0)
+    elif method == 'fastNlMeans':
+        # 非局部均值去噪（效果最好但较慢）
+        return cv2.fastNlMeansDenoisingColored(image, None, 10, 10, 7, 21)
+    return image
 
+
+def apply_enhancements(image, sharpness=True, contrast=True, denoise=True, 
+                       sharp_strength=1.5, contrast_alpha=1.2, contrast_beta=10, 
+                       denoise_method='bilateral'):
+    """
+    应用所有图像增强
+    :param image: 输入图像（BGR格式）
+    :param sharpness: 是否锐化
+    :param contrast: 是否增强对比度
+    :param denoise: 是否去噪
+    :param sharp_strength: 锐化强度
+    :param contrast_alpha: 对比度系数
+    :param contrast_beta: 亮度调整
+    :param denoise_method: 去噪方法
+    :return: 增强后的图像
+    """
+    enhanced = image.copy()
+    
+    if denoise:
+        enhanced = denoise_image(enhanced, denoise_method)
+    
+    if contrast:
+        enhanced = enhance_contrast(enhanced, contrast_alpha, contrast_beta)
+    
+    if sharpness:
+        enhanced = enhance_sharpness(enhanced, sharp_strength)
+    
+    return enhanced
+
+
+def set_camera_properties(cap, brightness=None, contrast=None, saturation=None, 
+                          sharpness=None, gain=None, exposure=None):
+    """
+    设置采集卡硬件参数
+    :param cap: VideoCapture对象
+    :param brightness: 亮度 (0-100)
+    :param contrast: 对比度 (0-100)
+    :param saturation: 饱和度 (0-100)
+    :param sharpness: 锐度 (0-100)
+    :param gain: 增益 (0-100)
+    :param exposure: 曝光 (通常为负值，如-6)
+    """
+    props = {
+        cv2.CAP_PROP_BRIGHTNESS: brightness,
+        cv2.CAP_PROP_CONTRAST: contrast,
+        cv2.CAP_PROP_SATURATION: saturation,
+        cv2.CAP_PROP_SHARPNESS: sharpness,
+        cv2.CAP_PROP_GAIN: gain,
+        cv2.CAP_PROP_EXPOSURE: exposure,
+    }
+    
+    for prop, value in props.items():
+        if value is not None:
+            try:
+                cap.set(prop, value)
+                actual = cap.get(prop)
+                logger.info(f"  设置 {prop.name if hasattr(prop, 'name') else prop}: {value} -> 实际: {actual:.2f}")
+            except Exception as e:
+                logger.warning(f"  ⚠️ 设置参数 {prop} 失败: {e}")
+
+
+def yolo_shibie(im_PIL, im_opencv_rgb, raw_frame_bgr, detections, model, show_original=True, 
+                enhance_enabled=False, enhance_params=None):
+    """
+    YOLO识别函数
+    :param im_PIL: PIL图像对象
+    :param im_opencv_rgb: RGB格式的OpenCV图像（裁剪后）
+    :param raw_frame_bgr: 原始BGR格式的OpenCV图像（未裁剪，与raw_frame.jpg一致）
+    :param detections: 检测结果字典
+    :param model: YOLO模型
+    :param show_original: 是否同时显示原始帧
+    :return: 更新后的detections字典，如果用户退出则返回None
+    """
+    if im_PIL is None:
+        return detections
+    
+    try:
+        results = model(im_PIL)
+        result = results[0]
+
+        # ✅ 获取绘制好框的图像（RGB格式）
+        frame_with_boxes_rgb = result.plot()
+        
+        # ✅ 转换为BGR格式用于OpenCV显示
+        frame_with_boxes_bgr = cv2.cvtColor(frame_with_boxes_rgb, cv2.COLOR_RGB2BGR)
+
+        # 应用图像增强（如果启用）
+        display_frame = frame_with_boxes_bgr.copy()
+        if enhance_enabled and enhance_params:
+            try:
+                display_frame = apply_enhancements(display_frame, **enhance_params)
+            except Exception as e:
+                print(f"⚠️ 图像增强失败: {e}")
+        
+        # 显示画面
+        if show_original and raw_frame_bgr is not None:
+            # 同时显示原始帧和检测结果（并排显示）
+            # 调整原始帧大小以匹配裁剪后的检测结果
+            h, w = display_frame.shape[:2]
+            # 裁剪原始帧（与get_frame的处理一致：30:30+720, 0:1280）
+            raw_height, raw_width = raw_frame_bgr.shape[:2]
+            crop_top = 30
+            crop_bottom = min(crop_top + h, raw_height)
+            crop_right = min(w, raw_width)
+            raw_cropped = raw_frame_bgr[crop_top:crop_bottom, 0:crop_right]
+            
+            # 如果尺寸不匹配，调整原始帧大小
+            if raw_cropped.shape[:2] != (h, w):
+                raw_cropped = cv2.resize(raw_cropped, (w, h))
+            
+            # 并排显示：原始帧(左) | 检测结果(右)
+            # 原始帧已经是BGR格式，检测结果也是BGR格式，可以直接拼接
+            combined = cv2.hconcat([raw_cropped, display_frame])
+            cv2.imshow("Original BGR (Left) | YOLO Detection (Right)", combined)
+        else:
+            # 只显示检测结果
+            cv2.imshow("YOLO Real-time Detection", display_frame)
+
+        # ✅ 提取检测信息
+        if result.boxes is not None and len(result.boxes.xyxy) > 0:
+            for i in range(len(result.boxes.xyxy)):
+                try:
+                    left = float(result.boxes.xyxy[i][0])
+                    top = float(result.boxes.xyxy[i][1])
+                    right = float(result.boxes.xyxy[i][2])
+                    bottom = float(result.boxes.xyxy[i][3])
+                    cls_id = int(result.boxes.cls[i])
+                    label = result.names[cls_id]
+
+                    if label in ['center', 'next', 'npc1', 'npc2', 'npc3', 'npc4', 'boss', 'zhaozi']:
+                        player_x = int(left + (right - left) / 2) + 3
+                        player_y = int(top + (bottom - top) / 2) + 40
+                        detections[label] = [player_x, player_y]
+                    elif label in ['daojv', 'gw']:
+                        player_x = int(left + (right - left) / 2) + 3
+                        player_y = int(top + (bottom - top) / 2) + 40
+                        # 确保列表存在
+                        if label not in detections:
+                            detections[label] = []
+                        detections[label].append([player_x, player_y])
+                except Exception as e:
+                    print(f"⚠️ 处理检测框时出错: {e}")
+                    continue
+
+    except Exception as e:
+        print(f"⚠️ YOLO检测出错: {e}")
+    
     return detections
 
 
-while True:
-    detections = {
-        'center': None, 'next': None,
-        'npc1': None, 'npc2': None, 'npc3': None, 'npc4': None,
-        'boss': None, 'zhaozi': None,
-        'daojv': [], 'gw': []
-    }
+def main():
+    """主函数"""
+    print("="*60)
+    print("YOLO实时检测测试")
+    print("="*60)
+    
+    # 从配置加载采集卡设置
+    active_group = config_manager.get_active_group()
+    
+    if active_group is None:
+        print("⚠️ 没有活动的配置组，使用默认设置")
+        print("提示: 可以运行 python gui_config.py 设置配置")
+        cam_index = 0
+        width = 1920
+        height = 1080
+    else:
+        print(f"📋 使用配置组: {active_group['name']}")
+        cam_index = active_group['camera_index']
+        width = active_group['camera_width']
+        height = active_group['camera_height']
+    
+    print(f"   采集卡索引: {cam_index}")
+    print(f"   分辨率: {width}x{height}")
+    print()
+    
+    # 初始化采集卡
+    print("🔧 正在初始化采集卡...")
+    get_image = GetImage(
+        cam_index=cam_index,
+        width=width,
+        height=height
+    )
+    
+    if get_image.cap is None:
+        print("❌ 采集卡初始化失败")
+        print("请检查：")
+        print("1. 采集卡是否正确连接")
+        print("2. 采集卡索引是否正确")
+        print("3. 采集卡驱动是否安装")
+        return
+    
+    # 设置采集卡硬件参数以提高清晰度（可选）
+    print("\n🔧 设置采集卡参数以提高清晰度...")
+    print("提示: 可以根据实际情况调整这些参数")
+    set_camera_properties(
+        get_image.cap,
+        brightness=50,      # 亮度 (0-100)
+        contrast=50,         # 对比度 (0-100)
+        saturation=55,      # 饱和度 (0-100)
+        sharpness=60,       # 锐度 (0-100，提高清晰度)
+        gain=None,          # 增益 (根据实际情况调整)
+        exposure=None       # 曝光 (根据实际情况调整，通常为负值)
+    )
+    
+    print("✅ 采集卡初始化成功")
+    print("\n快捷键:")
+    print("  'q' 或 ESC - 退出")
+    print("  'o' - 切换原始帧对比模式")
+    print("  'e' - 切换图像增强")
+    print("  '1'/'2' - 调整锐化强度 (+/-0.1)")
+    print("  '3'/'4' - 调整对比度 (+/-0.1)")
+    print()
+    
+    try:
+        frame_count = 0
+        show_original = True  # 默认同时显示原始帧和检测结果
+        enhance_enabled = False  # 默认关闭图像增强
+        
+        # 图像增强参数
+        enhance_params = {
+            'sharpness': True,
+            'contrast': True,
+            'denoise': True,
+            'sharp_strength': 1.5,
+            'contrast_alpha': 1.2,
+            'contrast_beta': 10,
+            'denoise_method': 'bilateral'
+        }
+        
+        while True:
+            # 获取帧
+            frame_data = get_image.get_frame()
+            
+            if frame_data is None:
+                print("⚠️ 无法获取帧，跳过...")
+                continue
+            
+            # frame_data 是 [im_opencv_rgb, im_PIL] 格式
+            # im_opencv_rgb 已经是RGB格式（经过BGR2RGB转换）
+            im_opencv_rgb, im_PIL = frame_data
+            
+            if im_PIL is None:
+                print("⚠️ PIL图像为空，跳过...")
+                continue
+            
+            # 获取原始BGR帧（与test_capture_card.py保存的raw_frame.jpg一致）
+            raw_frame_bgr = None
+            if get_image.cap is not None and get_image.frame is not None:
+                raw_frame_bgr = get_image.frame.copy()  # 原始BGR格式，未裁剪
+            
+            # 初始化检测结果字典
+            detections = {
+                'center': None, 'next': None,
+                'npc1': None, 'npc2': None, 'npc3': None, 'npc4': None,
+                'boss': None, 'zhaozi': None,
+                'daojv': [], 'gw': []
+            }
+            
+            # 执行YOLO检测
+            detections = yolo_shibie(im_PIL, im_opencv_rgb, raw_frame_bgr, detections, model, 
+                                    show_original, enhance_enabled, enhance_params)
+            
+            # 检查按键
+            key = cv2.waitKey(1) & 0xFF
+            if key in [27, ord('q'), ord('Q')]:
+                print("\n用户退出")
+                break
+            elif key == ord('o') or key == ord('O'):
+                show_original = not show_original
+                print(f"切换显示模式: {'原始帧对比' if show_original else '仅检测结果'}")
+            elif key == ord('e') or key == ord('E'):
+                enhance_enabled = not enhance_enabled
+                status = "开启" if enhance_enabled else "关闭"
+                print(f"图像增强: {status} (锐化={enhance_params['sharp_strength']:.1f}, "
+                      f"对比度={enhance_params['contrast_alpha']:.1f})")
+            elif key == ord('1'):
+                enhance_params['sharp_strength'] = min(3.0, enhance_params['sharp_strength'] + 0.1)
+                print(f"锐化强度: {enhance_params['sharp_strength']:.1f}")
+            elif key == ord('2'):
+                enhance_params['sharp_strength'] = max(0.5, enhance_params['sharp_strength'] - 0.1)
+                print(f"锐化强度: {enhance_params['sharp_strength']:.1f}")
+            elif key == ord('3'):
+                enhance_params['contrast_alpha'] = min(3.0, enhance_params['contrast_alpha'] + 0.1)
+                print(f"对比度: {enhance_params['contrast_alpha']:.1f}")
+            elif key == ord('4'):
+                enhance_params['contrast_alpha'] = max(0.5, enhance_params['contrast_alpha'] - 0.1)
+                print(f"对比度: {enhance_params['contrast_alpha']:.1f}")
+            
+            frame_count += 1
+            if frame_count % 30 == 0:  # 每30帧打印一次
+                print(f"📊 已处理 {frame_count} 帧")
+                # 打印有检测到的目标
+                detected_items = {k: v for k, v in detections.items() if v is not None and v != []}
+                if detected_items:
+                    print(f"   检测到: {detected_items}")
+    
+    except KeyboardInterrupt:
+        print("\n\n用户中断测试")
+    except Exception as e:
+        print(f"\n❌ 测试过程中发生错误: {e}")
+        import traceback
+        traceback.print_exc()
+    finally:
+        # 清理资源
+        get_image.release()
+        cv2.destroyAllWindows()
+        print("🔚 测试结束")
 
-    im_opencv = get_image.get_frame()  # [RGB, PIL]
-    detections = yolo_shibie(im_opencv[1], detections)
 
-    if detections is None:  # 用户退出
-        break
-
-    print(detections)
-
-cv2.destroyAllWindows()
+if __name__ == "__main__":
+    main()